The ‘Information Loop’ Mechanism on Short Video Platforms: How Users Unconsciously Enter a State of Interest Solidification

Abstract

Short video platforms use algorithm-driven recommendations to enhance user engagement, but this creates an ‘information loop’, where users are repeatedly exposed to similar content, leading to interest solidification. This study examines how algorithmic filtering, user behavior, and psychological reinforcement contribute to content homogeneity, reinforcing cognitive biases, echo chambers, and reduced critical thinking. Data analysis shows that TikTok has a 67% content repetition rate, and algorithmic filtering can narrow content exposure within 15 minutes. Survey results indicate that 78% of users experience repetitive content, and 65% struggle to diversify their recommendations. The paper proposes solutions such as algorithmic transparency, user-driven content diversification, and media literacy education to counteract the risks of content polarization and ideological entrenchment. Addressing these challenges is essential for promoting a more balanced and open digital information ecosystem.